Please use this identifier to cite or link to this item: http://ir.mu.ac.ke:8080/jspui/handle/123456789/9910
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dc.contributor.authorKemei, Zachary-
dc.contributor.authorRotich, Titus-
dc.contributor.authorBitok, Jacob-
dc.date.accessioned2025-09-03T09:12:39Z-
dc.date.available2025-09-03T09:12:39Z-
dc.date.issued2024-10-
dc.identifier.urihttp://ir.mu.ac.ke:8080/jspui/handle/123456789/9910-
dc.description.abstractIn this paper, an age-structured model was used to model population dynamics, and make predictions through simulation using 2019 Kenya population data. The age-structured mathematical model was developed, using partial differential equations on population densities as functions of age and time. The population was struc- tured into 20 clusters each of 5 year interval, and assigned different birth and death rate parameters. Crank- Nicolson numerical scheme was used to simulate the model and the 2019 initial population of 38,589,011 was found to increase by 50% to 57,956,100 by 2050. The initial economic dependency ratio was computed to be 1:2, but due to changes in technology and improvement of living standards, the new ratio is lowered to 1:1.14. The graphical presentation showed a trend of transition from expansive to constrictive population pyramiden_US
dc.language.isoenen_US
dc.publisherwww.iosrjournals.orgen_US
dc.subjectAge-Structured;en_US
dc.subjectDependency ratio;en_US
dc.titleModelling population dynamics using age-structured system of partial differential equationsen_US
dc.typeArticleen_US
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